It’s official – we are surrounded by oceans of data. We get daily Twitter trends, Facebook threads, likes, follower counts, re-tweets, mentions, clicks, visitor counts and RSS feeds. I am observing that many people now draw somewhat significant conclusions from these data points – they try to evaluate the effectiveness of their business, their brand and even the effectiveness of their workforce based on numerous social data points that clutter their browsers. Here are 5 things that are wrong with this trend:

Most of this data is actually nothing but “data puke”. Avinash Kaushik, Google’s Analytics Evangelist and author agrees. You see, the number of Twitter followers is not a meaningful attribute of influence. The number of Twitter “listeners” – those who are tuned in, is a better way to measure the effectiveness of the message that you send.

Most data sources on the web measure clicks and not behavior. Behavior on the web is clicks, right? Wrong! True attributes of behavior on the web combine what you click on with what you’ve done after you landed on the destination page. Watch out for clicks – they don’t equal engagement.

Engagement and audience size are not the same things. Remember that history lecture a while back in college. With 150 students in the hall, all focused on the professor, (with some exceptions) engagement pretty much equaled the size of the audience. In social web, audience never equals engagement. Over 40% of Twitter “users” haven’t logged in for the past 30 days. Over 50% haven’t logged in for the past 14 days.

Social platforms are guilty. It isn’t a big surprise that we are so fascinated with social data that turns out to be nothing but puke – all of the social platforms out there seem to push it on us. Dear Twitter, instead of telling me how many new followers I got today, can you please tell me how many people read the content that I shared? Oh, I have to pay for that? Is free information all of a sudden dangerously faulty? It seems like we need to ask ourselves this question, particularly as it relates to the social web.

Businesses beware – basing decisions on data puke will result in even more nausea. I know a CEO who measures the effectiveness of her social marketing team purely based on follower counts. I know at least a few community managers who aim at nothing else but more retweets. Hell, I know HR leaders who track social influence of their employees based purely on meaningless bits of information they find on Facebook. Some even partly base their hiring decisions on it. There is even an influence scoring engine that still considers me to be an “Explorer” of the social web. This same influence scoring engine tells me that one of my most frequently contributed topics has to do with “Colorado”. That’s ‘helpful’ – especially because I don’t believe I’ve said the word “Colorado” at all.

What it seems like we need the most these days is meaning associated with countless social data. Measure engagement, not followers. Measure true influence, not the imagined one. Measure value, not clicks.

Your thoughts? What are some of the effective social analytics for you?

Maksim is an executive in the areas of product management, product strategy and product marketing. He is a thought leader in the areas of business execution and business productivity software and an innovative product evangelist in the software industry. Maksim’s interests include making social software business-relevant and building beautiful SaaS tools for the purposes of improving productivity in key areas of enterprise operations - human resources, CRM and mobile. He blogs at Get Maksimized.

One response to “Data Value vs. Data Puke (In Social Web)”

Couldn’t agree more. That’s why I like the concept of “From content to commerce” where by creating amazing content we can promote sharing and then measure engagement, true influence, and value to properly assess ROI (e.g. How many sold tickets are the result of the engagement generated by a particular content strategy?). Today’s tools are not advanced or mature enough to give organizations an easy way to connect the dots.